Future-Proof Healthcare: Making Hospitals Energy Efficient
By Anandvardhan Singh
Powering Healthcare
Hospitals are dynamic energy-intensive environments, where the relentless demand for power to support life-saving equipment and maintain sterile conditions translates into substantial operational costs and critical safety concerns. While the average hospital consumes ₹4,75,00,000 (5 million kWh) worth of energy every year, the largest consumer is often overlooked. A significant chunk of this energy is consumed by HVAC (Heating, Ventilation, and Air Conditioning) systems, which are crucial for ensuring comfort and safety. With rising energy costs and increasing environmental concerns, and as highlighted in IPCC’s Sixth Assessment Report(AR6), energy efficiency is the singular lowest hanging fruit when it comes to the feasibility of climate control measures and alternatives. This article explores the heavy energy footprint of HVAC systems in hospitals, the potential for energy savings, and how ML and IoT technologies can revolutionise energy management in these critical facilities.
Energy Consumption in Hospitals
Hospitals are highly energy intensive, with HVAC systems accounting for >50% of total energy use, sometimes higher in extreme climates like Rajasthan. This significant consumption underscores the need for optimising HVAC systems to maintain strict temperature and humidity controls and improve energy efficiency.
In regions such as Rajasthan, HVAC energy use can reach up to 70% due to high cooling demands, whereas in milder regions like Banglore, it might be around 30%. These variations highlight the influence of climate, building design, and operational practices on energy consumption.
Implementing automated and optimised HVAC systems can reduce energy use by 20-40%, leveraging leading design practices, technical proficiency, and ML Powered IoT technologies for real-time monitoring and adjustments. This not only cuts costs but also enhances indoor air quality and patient comfort, contributing to better overall hospital performance and sustainability.
Core Challenges: Inefficient Design and Suboptimal Operations
Conventionally, all hospitals and large industrial complexes are consistently and systematically ill-designed, which sets these facilities up for failure from the get-go. This ranges from poor asset selection, inflated or cookie-cutter cooling specifications, and incorrectly placed incentives on the consulting and designing processes. Additionally, traditional operational methods, which rely on rigid schedules and manual adjustments, are highly inefficient because they fail to adapt to environmental changes and dynamic conditions. This inflexibility not only results in significantly higher energy consumption but also severely reduces the lifespan of assets.
The fundamental corrective measure in creating an integrated efficient cooling system is to have expert, industry leading design practices to optimally design HVAC systems for all geographies, local conditions, and the layout of said complex. In a short targeted audit, we identified 15 to 20 immediately actionable measures that can reduce energy consumption by 10% while simultaneously extending the equipment's operational lifetime. These measures address inefficiencies and optimise the system's performance, ensuring energy-efficient and sustainable operation.
While operations are the most overlooked while setting up an HVAC system, they account for 70% of the total cost of the system over a period of 10 years, with the initial CapEx that is generally heavily critiqued is a minority. These neglected industrial cooling systems contribute to a huge 10% share of the total carbon emissions in the country. Our integrated approach makes it so that the facilities get a fixed, industry-lowest charge for their cooling consumption, and can focus on what they do best.
Introducing Passive cooling technologies to reduce the heat load of buildings
In a traditional HVAC design, the entire building is modelled for active centralised heating & cooling systems which are expensive and as we’ve discovered, inefficiently operated. Reducing the peak heat load demand in buildings by incorporating passive cooling technologies like radiant cooling brings down the energy consumption of these central HVAC units. Radiant cooling is an example of an innovative and energy-efficient technology used for cooling buildings passively, and is up to 50% more efficient when compared to traditional cooling methods. Utilising this method, we can cool indoor spaces by removing heat from surfaces (such as ceilings, walls, or floors) rather than by directly cooling the air. It relies on the principle of radiant heat transfer, where heat is transferred from warmer surfaces to cooler ones through electromagnetic waves (radiation). This method offers a comfortable and even distribution of cooling without the need for large, expensive and specialised equipment, in these specific conditions.
Implementing ML and IoT for Energy Savings
Implementing ML and IoT in HVAC systems involves establishing a robust infrastructure capable of supporting advanced technologies. This begins with the deployment of IoT sensors throughout the hospital to monitor critical parameters such as temperature, humidity, and air quality. These sensors provide the real-time data needed for ML algorithms to function effectively. Machine learning algorithms then process this data, learning from patterns to make precise adjustments to the HVAC system. This includes predictive maintenance, which can prevent system breakdowns and optimise performance, as well as adaptive control to ensure energy is used efficiently.
For instance, sensors placed in various locations within a hospital can detect fluctuations in occupancy, temperature, and humidity. These sensors feed data into a central system where ML algorithms analyze it in real-time. Based on this analysis, the system can make informed decisions such as adjusting air flow, changing thermostat settings, or scheduling maintenance activities before any issues become critical. This approach not only reduces energy consumption but also enhances system performance and reliability. Our case studies have shown that hospitals implementing ML-driven intelligent HVAC management can achieve significant energy savings. For instance, Hospital A in Mumbai reduced its HVAC energy consumption by 30% after switching to ML, and Hospital B in Delhi saw a 25% decrease. These examples illustrate the substantial impact that Technology can have on reducing energy usage in hospital HVAC systems.
Paving the way for Smarter Hospitals
Reducing energy consumption in hospitals is a critical goal, both for cost savings and environmental sustainability. HVAC systems, as major energy consumers, present a significant opportunity for improvement. By leveraging inter-disciplinary excellence and decade-long experience with facilities across the nation, we have seen an impact of 139,000 tons CO2e reduced, which would’ve taken 8.5 Million trees over a year to capture. It is imperative for hospital administrators and policymakers to invest in these advanced technologies, driving the future of energy efficiency in healthcare. The benefits are clear: reduced energy consumption, lower costs, and a healthier environment for patients and staff alike.
The future of energy management in hospitals lies in smart, responsive systems that can adapt to the ever-changing demands of healthcare environments. Besides deliberate and effective design for these unique cooling systems, embracing ML and IoT in hospitals can achieve significant energy savings while providing better care for patients. This not only helps in managing operational costs but also aligns with global efforts to combat climate change. As technology continues to evolve, the potential for further improvements in energy efficiency and sustainability will only grow, making now the perfect time for hospitals to begin this transformative journey.
Author : Anandvardhan Singh
Product Manager, SmartJoules